Find the best oracle for a task. Considers trust, capabilities, availability. Returns ranked candidates.
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | What you need (e.g. sanctions screening, DORA audit) | |
| constraints | No | Optional: {min_trust_grade, max_cost_usdc} |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that the tool considers trust, capabilities, and availability and returns ranked candidates, which is valuable behavioral context. However, it does not mention side effects, read-only nature, or any limitations, so transparency is moderate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences, front-loaded with the main action, and every sentence adds value. There is no redundancy or fluff, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (2 params, no output schema, no annotations), the description covers the purpose, decision criteria, and return type. However, it lacks detail on the structure of the returned candidates and does not explicitly address edge cases or usage context relative to siblings. Still, it is sufficiently complete for routine routing tasks.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for both parameters (task and constraints). The description adds context that trust and cost are considered, aligning with constraints, but it does not significantly enhance parameter understanding beyond what the schema already provides. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Find' and clearly identifies the resource ('the best oracle for a task'), plus lists the criteria considered (trust, capabilities, availability) and the output (ranked candidates). This distinguishes it from sibling tools like quantum_ask or quantum_deal, which likely perform different actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need to select an oracle for a task, but it does not explicitly state when to use this tool versus alternatives. With many sibling tools, the lack of direct exclusions or alternative names leaves the agent to infer appropriate use, which is adequate but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools have unclear boundaries: quantum_ask and quantum_intent both serve as natural language 'front doors' with similar descriptions, and quantum_route and quantum_refer both find the best oracle for a task. This creates significant overlap that could cause agents to select the wrong tool.
Most tools follow a consistent quantum_<verb_or_noun> snake_case pattern (e.g., quantum_join, quantum_execute, quantum_settle). The single exception is neural_status, which breaks the prefix convention, but overall the naming is predictable and readable.
With 20 tools, the server sits in the heavy range (16-25). While the broad scope of OracleNet (intelligence, natural language, deals, reputation, subscriptions, scanning) somewhat justifies the count, it feels overpacked and could be streamlined by merging overlapping tools.
The tool surface covers core workflows: joining, querying status/nodes/reputation, routing, executing, dealing, settling, rating, and subscribing. However, lifecycle gaps exist—no unsubscribe, leave/delete node, deal cancellation, or dispute resolution—which can leave agents with dead ends.